CAP Evaluation Insights: organic farming

This edition of CAP Evaluation Insights offers a detailed synthesis of 60 evaluations conducted by Member States and the UK between 2018 and 2025, focusing on the effectiveness of CAP support for organic farming. These evaluations assess how Rural Development Programmes (RDPs) – and particularly Measure 11 implemented from 2014 to 2022 – have contributed to the expansion of organic agriculture, as well as its environmental and socioeconomic impacts.

While these evaluations provide valuable insights into the performance of CAP support for organic farming, they also highlight significant methodological and data-related challenges.

The in-depth appraisal of selected evaluations revealed a wide variety of methodologies. Quantitative approaches included econometric techniques such as difference-in-differences, panel regressions and matching algorithms for counterfactual analysis, often complemented by spatial analysis. Qualitative methods – surveys, interviews and case studies – captured farmer experiences and contextual factors. Some evaluations, such as those from Latvia and Schleswig-Holstein, demonstrated strong methodological rigour by combining panel data with econometric analysis to isolate the effects of organic support measures.

The report underscores the importance of a dual-focused evaluation framework, grounded in a clear intervention logic. This framework should distinguish between implementation analysis – examining adoption rates, payment levels, and eligibility criteria – and impact evaluation, which assesses the contribution of organic farming to CAP objectives such as biodiversity conservation, climate mitigation and rural development.

Several recurring methodological challenges emerged. Chief among them was the difficulty of constructing reliable counterfactuals for unbiased, appropriate comparison. Many evaluations struggled to establish causality and accurately attribute observed outcomes to CAP interventions, especially when multiple agri-environmental measures overlapped. Baseline data were often incomplete or constructed retrospectively, limiting the robustness of before-and-after comparisons.

Concerns over additionality and deadweight effects were also raised, with some evaluations questioning whether support genuinely incentivised new adoption or merely subsidised existing practices. Selection bias further complicated analysis, as organic farms often differed systematically from conventional ones in terms of location, size and management intensity.

Evaluations frequently reported difficulties in linking support databases with organic operator registers and in integrating environmental monitoring data. The lack of georeferenced data and limited long-term monitoring hampered the ability to conduct counterfactual analyses and track changes over time – particularly for the assessment of the permanence of environmental and economic benefits.

To overcome these limitations, experts recommend improving data integration, building panel datasets and enhancing the quality and granularity of indicators.

The development of clear intervention logics is seen as essential for improving the reliability and policy relevance of future evaluations.

Addressing these will be very crucial for ensuring that future evaluations can more accurately measure the effectiveness of policy interventions and optimise the contribution of organic farming to sustainability goals.